The field of the invention is systems and methods for magnetic resonance imaging (“MRI”). More particularly, the invention relates to systems and methods for automatically segmenting images acquired with an MRI system, such as images of the breast.
Breast cancer is currently the most common diagnosed cancer among women and a significant cause of death. Breast density, a representation of the amount of dense parenchyma present in the breast, has been identified as a significant risk factor for developing breast cancer. Although the majority of epidemiological evidence on breast density as a risk factor comes from x-ray mammography screening data, some researchers have acknowledged the advantages of studying breast density with different imaging modalities, such as MRI. MRI is a versatile imaging modality that provides a three-dimensional view of the breast for volumetric breast density assessment without the risks from exposure to ionizing radiation.
However, quantitative evaluation of breast density using MRI suffers from several limitations, including inconsistent breast boundary segmentation and lack of standardized algorithms to accurately measure breast density. It is desirable to have consistent and robust computer-aided analysis tools to segment the breast and to extract the total volume of the breast in three dimensions.
For quantitative assessment of breast density using MRI, separate images of breast water and fat can be obtained and breast water can be measured as a surrogate for fibroglandular tissue and stroma. However, with these techniques, breast segmentation is further necessary to remove background noise artifacts and exclude surrounding muscle tissues in the chest wall. Robust and reliable automatic segmentation is, therefore, desired. In breast MRI, image intensity distributions are dependent on the selected MRI scanning protocol and acquisition parameters; thus, segmentation based on the separation of grayscale intensities, such as selective thresholding, is inadequate and lacks generalization when used with different scanning protocols. In addition, the contrast between the breast and adjacent structures, such as pectoral muscles, is not distinctively defined.
It is therefore desired to provide a method for segmenting breast tissue from a three-dimensional image acquired with MRI, in which the segmentation does not rely on grayscale intensity differences in the image, and in which images acquired with different scanning protocols can be similarly segmented for reliable comparisons.